Evidence map›Paper›PMID 38314719›Full record

SynthesisJournal of health psychology2024

Internal consistency reliability of the Revised Illness Perceptions Questionnaire: A systematic review and reliability generalization meta-analysis.

Eleanor Rivera, Kristin Levoy, Chang Park, Azucena Villalobos, Paige Martin, Min Jung Kim, Karen B Hirschman

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of health psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Eleanor RiveraUniversity of Illinois Chicago, USA.ORCID 0000-0002-3111-0611
Kristin LevoyIndiana University, USA.
Chang ParkUniversity of Illinois Chicago, USA.
Azucena VillalobosUniversity of Pennsylvania, USA.
Paige MartinUniversity of Pennsylvania, USA.
Min Jung KimYonsei University, South Korea.
Karen B HirschmanUniversity of Pennsylvania, USA.

Funding

Individualized Care for At Risk Older AdultsT32NR009356 · NINR · UNIVERSITY OF PENNSYLVANIA · PI Lauren M Massimo, MARY D NAYLOR · 2007 to 2026
$7.8M
NINR NIH HHS T32 NR009356
6 · The paper itself

Abstract

The Revised Illness Perception Questionnaire (IPQ-R) assesses patients' perspectives of their illnesses. Original psychometric testing occurred in limited populations. The purpose of this reliability generalization meta-analysis was to: (1) estimate internal consistency reliability of each IPQ-R subscale, and (2) test moderators of these estimates. Web of Science was searched in July 2022 for articles citing the original IPQ-R paper that reported IPQ-R reliability data. Cronbach's alphas (⍺) were pooled for each IPQ-R subscale using inverse variance weighting and DerSimonian and Laird estimation. Sixty-six studies met criteria. Overall pooled ⍺ estimates were acceptable: 0.71-0.87. Treatment control reliability was reduced among cardiac (⍺ = 0.68), diabetes/kidney disease (⍺ = 0.63), and mixed/other (⍺ = 0.66) samples; cyclical reliability was reduced in cancer (⍺ = 0.65) samples. Age, gender, and race were also significant moderators. Subscale reliability varied based on sample characteristics. Adapting IPQ-R subscales to account for sample variation could improve measurement of illness perception constructs.

Indexed as

PsychometricsHumansReproducibility of ResultsSurveys and Questionnaireschronic diseaseillness perceptionillness representationmeta-analysisreliability

Identifiers

PMID38314719
PMCPMC13131025

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.